Thomas Huet (Dr.)

Prehistory and Computational Archaeology. My main research projects cover the Neolithic of Western Asia and its embedded iconography

LabEx ARCHIMEDE, Associate Researcher UMR 5140 ASM-CNRS, Université Paul-Valéry Montpellier 3, France

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PROJECTS

                   



There is probably a natural history of human societies. Quetelet’s concept of “average man” (homme moyen) or Tobler’s first law of geography, show that parsimonial, multiscalar, bottom-up and agglomerative methods are suitable to describe data and datasets. Multifactorial, unsupervised and data-driven analysis are favored since we did not know, a priori, what aspects and at which scale (from the settlement to the continent) will give the positive results. The recurrent and relevant patterns will be identified a posteriori. Historical sciences operate by comparison, evaluating the similarities and the differences between two or more autonomous populations, groups, cultures, settlements, etc. The archaeological investigation can be divided into 4 dimensions (W4) to address the questions ‘Why?’ and ‘How?’) evoluate past societies:

  • ‘What?’ (culture) participate to the historical processes
  • ‘Where?’ (geography) did these historical processes occurred
  • ‘When?’ (time) did these processes historical occurred
  • ‘Who?’ (genetic) participate to these historical processes

The Cartesian product of these lines of evidence are resumed in my web docs under the concept of Gene-Culure coevolution.


Statistical approach

H0 and H1

The hypothesis H0 is the null hypothesis, normal distribution, homogeneity of variances, same populations, etc., its W4 variants are:

  • ‘What?’: cultural consensus, homophily, homogeneity of cultural traits, social affinity, social proximity, cultural affinity, cultural proximity, etc.
  • ‘When?’: time continuity principle, gradual patterns, etc.
  • ‘Where?’: space continuity principle, homogeneous space, isotropic space, etc.
  • ‘Who?’: molecular clock, random genetic drifts, population continuity, PC, neutral mutation, genetic drift alone, mutation dans le temps, etc.

The opposite hypothesis is the H1 hypothesis. Its W4 variants are:

  • ‘What?’: cultural evolution, ethnicity, cultural change, heterogeneity of cultural traits, dérive historique, etc.
  • ‘When?’: emergence, etc.
  • ‘Where?’: heterogeneous space, anisotropic space, etc.
  • ‘Who?’: genetic dissimilarity, genetic distance, demic diffusion, etc.

What

“Cultural consensus leads to ethnicity” (Juan Anton Barceló Alvarez)

Cultural identity is the product of a set of cultural traits. Cultural traits are considered in terms of presence/absence, relative quantities and correlations of various items belonging to material (raw material, settlements, etc.) and practices (technical, symbolic, etc.). A cultural trait can be shared (at different degrees), or not, by different groups. Renfrew and Bahn (1991)[1] have modeled the different cultural subsystems:

subsystem description
subsistence interactions around food resources
technological set of chaines opératoires for artifacts production
social set of inter-individuals and intra-group interactions
symbolic languages, picture production, religions, etc.
external trade trade exchanges inter-groups
demographic population size (scale factor)
ecological set of natural features

Study of archaeological cultures will permit to respond to the question: ‘What ?’. It will contribute to define the cultural identity of the social groups. For example, Impressa-Cardial complex (ICC) is named after its ceramic characteristics (impressed and cardium decorations) and is associated to different cultural traits: settlement particularities (e.g. proximity to sea shore), production economy (e.g. wheat, domestic goats), specific diet (cereal-based consumption), etc. There is no consensus on which cultural traits (e.g. ceramic productions, settlements system, diet) have to be selected in order to compare and measure cultural (dis)similarities. Each selection of these traits will have to be explicitly justified. Commonly, cultural traits will be selected into the different subsystems of a social group organization [1]: subsistence (e.g. relative % of domestic and wild animals consumption), technological (e.g. presence/absence of loom weights), social (e.g. social hierarchy), symbolic (e.g. iconography), external trade (e.g. presence/absence of long-distance exchanges) and demographics (e.g. average ages of death). A key notion, for the cultural dimension, is the notion of chaîne opératoire (CO). The CO is a sequence of technical gestures, following the same order, that transform the raw material into a usable product [2]. Beside the technical constraints (i.e. the technical efficiency), the more complex is the CO, the less likely two different cultures could share the same CO without having any previous cultural interactions (i.e. trait-adoptions). In this way, complex COs are close to the notion of style: a "highly specific and characteristic manner of doing something (...) always peculiar to a specific time and place" [3]. Studies of complex COs cover numerous fields of social activities (e.g. acquisition, production, shaping, trade and use of lithic materials) and are key values concerning the recognition of trait-adoptions. Just like significant changes in the demographic subsystem imply significant changes in the social organization [4], restructuration of ceramic decorations reflect a cultural shift [5] and changes in complex COs reflect also social changes. Within others cultural traits, a social group is defined by its diet and its type of mobility. Isotopes analysis permit to work on mobility (isotopes of Pb, Sr and O), diet (N and C) and seasonality (Sr and O). As an example, isotopic analyses on mobility of Linearbandkeramik complex (LBK), partly confirmed by the DNA analyses, show that women have generally a higher rank of mobility (nonlocal women) than men [6]. The main reason seems to be linked to the matrimonial regime (patrilocal) [7] [8]. Diet isotopes, permit to enlighten cultural traits for a given group. For example, during the first part of ICC Neolithic diffusion (Impressed ware period) the Neolithic incomers have a terrestrial diet (relative high levels of 15N and low levels of 13C isotopes are linked with meat consumption), without any maritime product, although the sites are significantly close to the seashore [9]. Seasonality isotopes are specially interesting to study mobility of foragers groups (multiseasonal circulating mobilities with a relocation of the residential base), transhumance practices, etc. Isotopes are space-dependent, they can be studied geographically, taking into account the geology, land cover, etc., and spatial analysis, site catchments, shorter paths, etc. Once selected identical cultural traits in different groups, (dis)similarities between these groups will be measured in R with appropriated packages, functions or indexes: Bray-Curtis coefficient for contingency tables, Jaccard index for presence/absence tables, etc.

Iconography

Iconography represent a part of the symbolic subsystem. The R package iconr helps to model iconographic content with Graph theory and GIS. This package will allow to ground common methods to study iconography over the long-term and at the larger scale (example)

Where

Que les valeurs d’un caractère ne se répartissent pas n’importe comment dans l’espace signifie qu’il existe une organisation spatiale” (Groupe Chadule 1997)

project

Spatialization will permit to respond to the question: ‘Where ?’. Spatial distributions of social groups are the result of historical processes. Different R packages permit to manage both geographical and network analyses (example).

When

project

Development of datasets, webpages, interactive apps functions with R for absolute date data management (collect, spatialization, calibration, grouping, analysis, modeling).

Who

project

Genetic identity of a population is its genetic signature. Genetic analysis permit to evaluate genetic populations similarities by comparison of ancient DNA (aDNA) sequences.

Why

And how… According to Mauss, “the social domain is the domain of modality” (Mauss 1930). For Bourdieu (1977), the habitus is the “generative principle of regulated improvisions”.

References

[1] Renfrew, C.,& Bahn, P. G. (1991). Archaeology: theories, methods and practice (Vol. 2). London: Thames and Hudson.

[2] Cresswell, R., & Bensa, A. (1996). A propos de la technologie culturelle: Entretien avec Robert Cresswell. Genèses, 120-136.

[3] Sackett, J. R. (1977). The meaning of style in archaeology: a general model. American antiquity, 42(3), 369-380.

[4] Bocquet-Appel, J. P. (2008). Explaining the Neolithic demographic transition. In The Neolithic demographic transition and its consequences (pp. 35-55). Springer, Dordrecht.

[5] Demoule, J. P. (1994). La céramique comme marqueur social: variabilité spatiale et chronologique. Terre cuite et société: la céramique, document technique, économique et culturel, Juans-les-Pins: Editions APDCA, 473-497.

[6] Shennan, S. (2018). The first farmers of Europe: an evolutionary perspective. Cambridge University Press.

[7] Brown, K. A. (2016). Women on the move. The DNA evidence for female mobility and exogamy in prehistory. Past mobilities archaeological approaches to movement and mobility, 155-174.

[8] Kristiansen, K., Allentoft, M. E., Frei, K. M., Iversen, R., Johannsen, N. N., Kroonen, G., … & Willerslev, E. (2017). Re-theorising mobility and the formation of culture and language among the Corded Ware Culture in Europe. antiquity, 91(356), 334-347.

[9] Lightfoot, E., Boneva, B., Miracle, P. T., Šlaus, M., & O’connell, T. C. (2011). Exploring the Mesolithic and Neolithic transition in Croatia through isotopic investigations. Antiquity, 85(327), 73-86.

[10] Nakoinz, Oliver & Knitter, Daniel. (2016). Modelling Human Behaviour in Landscapes - Basic Concepts and Modelling Elements. 10.1007/978-3-319-29538-1.

[11] Bramanti, B., Thomas, M. G., Haak, W., Unterländer, M., Jores, P., Tambets, K., … & Burger, J. (2009). Genetic discontinuity between local hunter-gatherers and central Europe’s first farmers. Science, 326(5949), 137-140.